End-to-end provisioning of storage clouds

ABSTRACT

Embodiments discussed in this disclosure provide an integrated provisioning framework that automates the process of provisioning storage resources, end-to-end, for an enterprise storage cloud environment. Such embodiments configure and orchestrate the deployment of a user&#39;s workload and, at the same time, provide optimization across a multitude of storage cloud resources. Along these lines, input is received in the form of workload requirements and configuration information for available system resources. Based on the input, a set (at least one) of storage cloud configuration plans is developed that satisfy the workload requirements. A set of scripts is then generated that orchestrate the deployment and configuration of different software and hardware components based on the plans.

RELATED U.S. APPLICATION DATA

The present patent document is a continuation of U.S. patent applicationSer. No. 12/857,005, filed Aug. 16, 2010, entitled “END-TO-ENDPROVISIONING OF STORAGE CLOUDS”. The disclosure of U.S. patentapplication Ser. No. 12/857,005 is incorporated herein by reference.

TECHNICAL FIELD

The present invention relates generally to storage provisioning.Specifically, the present invention relates to end-to-end provisioningof storage clouds.

BACKGROUND

The cloud computing environment is an enhancement to the predecessorgrid environment, whereby multiple grids and other computation resourcesmay be further abstracted by a cloud layer, thus making disparatedevices appear to an end-user as a single pool of seamless resources.These resources may include such things as physical or logical computeengines, servers and devices, device memory, storage devices.

Enterprise storage clouds are comprised of multiple layers of softwareand hardware components, all of which need to be correctly configuredfor proper functioning of the storage cloud service. For example, aNetwork Attached Storage (NAS)-based storage cloud is typicallycomprised of storage subsystems, inter-connection fabric (fiber channel,InfiniBand, Ethernet, etc.), storage nodes, interface nodes, filesystem, etc. System administrators have to rely on a litany ofmanagement tools to manage and configure these components individuallyand provision storage resources for end-users. Such independentmanagement may be costly, error-prone and time-consuming and may eitherresult in under-provisioning or suboptimal utilization of resources.

SUMMARY

Embodiments discussed in this disclosure provide an integratedprovisioning framework that automates the process of provisioningstorage resources, end-to-end, for an enterprise storage cloudenvironment. Such embodiments configure and orchestrate the deploymentof a user's workload and, at the same time, provide optimization acrossa multitude of storage cloud resources. Along these lines, input isreceived in the form of workload requirements and configurationinformation for available system resources. Based on the input, a set(at least one) of storage cloud configuration plans is developed thatsatisfy the workload requirements. A set of scripts is then generatedthat orchestrate the deployment and configuration of different softwareand hardware components based on the plans.

A first aspect of the present invention provides a method for end-to-endprovisioning of storage clouds, comprising: accessing a set of workloadrequirements and a set of system resource configurations for a set ofhardware and software components associated with a storage cloud;generating a set of plans for provisioning the storage cloud, each ofthe set of plans proposing an adjustment of the set of system resourceconfigurations so that the set of workload requirements are met; andgenerating a set of scripts to carry out the set of plans, the set ofscripts being configured to orchestrate a deployment and a configurationof the set of hardware and software components.

A second aspect of the present invention provides a system forend-to-end provisioning of storage clouds, comprising: a bus; aprocessor coupled to the bus; and a memory medium coupled to the bus,the memory medium comprising instructions to: access a set of workloadrequirements and a set of system resource configurations for a storagecloud; access a set of workload requirements and a set of systemresource configurations for a set of hardware and software componentsassociated with a storage cloud; generate a set of plans forprovisioning the storage cloud, each of the set of plans proposing anadjustment of the set of system resource configurations so that the setof workload requirements are met; and generate a set of scripts to carryout the set of plans, the set of scripts being configured to orchestratea deployment and a configuration of the set of hardware and softwarecomponents.

A third aspect of the present invention provides a computer programproduct for end-to-end provisioning of storage clouds, the computerprogram product comprising a computer readable storage media, andprogram instructions stored on the computer readable storage media, to:access a set of workload requirements and a set of system resourceconfigurations for a set of hardware and software components associatedwith a storage cloud; generate a set of plans for provisioning thestorage cloud, each of the set of plans proposing an adjustment of theset of system resource configurations so that the set of workloadrequirements are met; and generate a set of scripts to carry out the setof plans, the set of scripts being configured to orchestrate adeployment and a configuration of the set of hardware and softwarecomponents.

A fourth aspect of the present invention provides a method for deployinga system for end-to-end provisioning of storage clouds, comprising:providing a computer infrastructure being operable to: access a set ofworkload requirements and a set of system resource configurations for aset of hardware and software components associated with a storage cloud;generate a set of plans for provisioning the storage cloud, each of theset of plans proposing an adjustment of the set of system resourceconfigurations so that the set of workload requirements are met; andgenerate a set of scripts to carry out the set of plans, the set ofscripts being configured to orchestrate a deployment and a configurationof the set of hardware and software components.

BRIEF DESCRIPTION OF THE DRAWINGS

These and other features of this invention will be more readilyunderstood from the following detailed description of the variousaspects of the invention taken in conjunction with the accompanyingdrawings in which:

FIG. 1 depicts a cloud computing node according to an embodiment of thepresent invention.

FIG. 2 depicts a cloud computing environment according to an embodimentof the present invention.

FIG. 3 depicts abstraction model layers according to an embodiment ofthe present invention.

FIG. 4 depicts an architectural diagram according to an embodiment ofthe present invention.

FIG. 5 depicts a process flow diagram according to an embodiment of thepresent invention.

FIG. 6 depicts a method flow diagram according to an embodiment of thepresent invention.

The drawings are not necessarily to scale. The drawings are merelyschematic representations, not intended to portray specific parametersof the invention. The drawings are intended to depict only typicalembodiments of the invention, and therefore should not be considered aslimiting the scope of the invention. In the drawings, like numberingrepresents like elements.

DETAILED DESCRIPTION

Embodiments discussed in this disclosure provide an integratedprovisioning framework that automates the process of provisioningstorage resources, end-to-end, for an enterprise storage cloudenvironment. Such embodiments configure and orchestrate the deploymentof a user's workload and, at the same time, provide optimization acrossa multitude of storage cloud resources. Along these lines, input isreceived in the form of workload requirements and configurationinformation for available system resources. Based on the input, a set(at least one) of storage cloud configuration plans is developed thatsatisfy the workload requirements. A set of scripts is then generatedthat orchestrate the deployment and configuration of different softwareand hardware components based on the plans.

In this disclosure, it is assumed that the storage cloud is based onGeneral Parallel File Systems (GPFS), which provides a scalable andparallel access to backend storage consisting of a Storage Area Network(SAN). However, this need not be the case as similar techniques can alsobe applied to other cloud architectures as well. Moreover, it isunderstood in advance that although this disclosure includes a detaileddescription of cloud computing, implementation of the teachings recitedherein are not limited to a cloud computing environment. Rather,embodiments of the present invention are capable of being implemented inconjunction with any other type of computing environment now known orlater developed.

Cloud computing is a model of service delivery for enabling convenient,on-demand network access to a shared pool of configurable computingresources (e.g. networks, network bandwidth, servers, processing,memory, storage, applications, virtual machines, and services) that canbe rapidly provisioned and released with minimal management effort orinteraction with a provider of the service. This cloud model may includeat least five characteristics, at least three service models, and atleast four deployment models.

Characteristics are as follows:

On-demand self-service: a cloud consumer can unilaterally provisioncomputing capabilities, such as server time and network storage, asneeded, automatically without requiring human interaction with theservice's provider.

Broad network access: capabilities are available over a network andaccessed through standard mechanisms that promote use by heterogeneousthin or thick client platforms (e.g., mobile phones, laptops, and PDAs).

Resource pooling: the provider's computing resources are pooled to servemultiple consumers using a multi-tenant model, with different physicaland virtual resources dynamically assigned and reassigned according todemand. There is a sense of location independence in that the consumergenerally has no control or knowledge over the exact location of theprovided resources but may be able to specify location at a higher levelof abstraction (e.g., country, state, or datacenter).

Rapid elasticity: capabilities can be rapidly and elasticallyprovisioned, in some cases automatically, to quickly scale out andrapidly released to quickly scale in. To the consumer, the capabilitiesavailable for provisioning often appear to be unlimited and can bepurchased in any quantity at any time.

Measured service: cloud systems automatically control and optimizeresource use by leveraging a metering capability at some level ofabstraction appropriate to the type of service (e.g., storage,processing, bandwidth, and active user accounts). Resource usage can bemonitored, controlled, and reported providing transparency for both theprovider and consumer of the utilized service.

Service Models are as follows:

Software as a Service (SaaS): the capability provided to the consumer isto use the provider's applications running on a cloud infrastructure.The applications are accessible from various client devices through athin client interface such as a web browser (e.g., web-based email). Theconsumer does not manage or control the underlying cloud infrastructureincluding network, servers, operating systems, storage, or evenindividual application capabilities, with the possible exception oflimited user-specific application configuration settings.

Platform as a Service (PaaS): the capability provided to the consumer isto deploy onto the cloud infrastructure consumer-created or acquiredapplications created using programming languages and tools supported bythe provider. The consumer does not manage or control the underlyingcloud infrastructure including networks, servers, operating systems, orstorage, but has control over the deployed applications and possiblyapplication-hosting environment configurations.

Infrastructure as a Service (IaaS): the capability provided to theconsumer is to provision processing, storage, networks, and otherfundamental computing resources where the consumer is able to deploy andrun arbitrary software, which can include operating systems andapplications. The consumer does not manage or control the underlyingcloud infrastructure but has control over operating systems, storage,deployed applications, and possibly limited control of select networkingcomponents (e.g., host firewalls).

Deployment Models are as follows:

Private cloud: the cloud infrastructure is operated solely for anorganization. It may be managed by the organization or a third party andmay exist on-premises or off-premises.

Community cloud: the cloud infrastructure is shared by severalorganizations and supports a specific community that has shared concerns(e.g., mission, security requirements, policy, and complianceconsiderations). It may be managed by the organizations or a third partyand may exist on-premises or off-premises.

Public cloud: the cloud infrastructure is made available to the generalpublic or a large industry group and is owned by an organization sellingcloud services.

Hybrid cloud: the cloud infrastructure is a composition of two or moreclouds (private, community, or public) that remain unique entities butare bound together by standardized or proprietary technology thatenables data and application portability (e.g., cloud bursting forload-balancing between clouds).

A cloud computing environment is service oriented with a focus onstatelessness, low coupling, modularity, and semantic interoperability.At the heart of cloud computing is an infrastructure comprising anetwork of interconnected nodes.

Referring now to FIG. 1, a schematic of an example of a cloud computingnode is shown. Cloud computing node 10 is only one example of a suitablecloud computing node and is not intended to suggest any limitation as tothe scope of use or functionality of embodiments of the inventiondescribed herein. Regardless, cloud computing node 10 is capable ofbeing implemented and/or performing any of the functionality set forthhereinabove.

In cloud computing node 10, there is a computer system/server 12, whichis operational with numerous other general purpose or special purposecomputing system environments or configurations. Examples of well-knowncomputing systems, environments, and/or configurations that may besuitable for use with computer system/server 12 include, but are notlimited to, personal computer systems, server computer systems, thinclients, thick clients, hand-held or laptop devices, multiprocessorsystems, microprocessor-based systems, set top boxes, programmableconsumer electronics, network PCs, minicomputer systems, mainframecomputer systems, and distributed cloud computing environments thatinclude any of the above systems or devices, and the like.

Computer system/server 12 may be described in the general context ofcomputer system-executable instructions, such as program modules, beingexecuted by a computer system. Generally, program modules may includeroutines, programs, objects, components, logic, data structures, and soon, that perform particular tasks or implement particular abstract datatypes. Computer system/server 12 may be practiced in distributed cloudcomputing environments where tasks are performed by remote processingdevices that are linked through a communications network. In adistributed cloud computing environment, program modules may be locatedin both local and remote computer system storage media including memorystorage devices.

As shown in FIG. 1, computer system/server 12 in cloud computing node 10is shown in the form of a general-purpose computing device. Thecomponents of computer system/server 12 may include, but are not limitedto, one or more processors or processing units 16, a system memory 28,and a bus 18 that couples various system components including systemmemory 28 to processor 16.

Bus 18 represents one or more of any of several types of bus structures,including a memory bus or memory controller, a peripheral bus, anaccelerated graphics port, and a processor or local bus using any of avariety of bus architectures. By way of example, and not limitation,such architectures include Industry Standard Architecture (ISA) bus,Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA) bus, VideoElectronics Standards Association (VESA) local bus, and PeripheralComponent Interconnects (PCI) bus.

Computer system/server 12 typically includes a variety of computersystem readable media. Such media may be any available media that isaccessible by computer system/server 12, and it includes both volatileand non-volatile media, removable and non-removable media.

System memory 28 can include computer system readable media in the formof volatile memory, such as random access memory (RAM) 30 and/or cachememory 32. Computer system/server 12 may further include otherremovable/non-removable, volatile/non-volatile computer system storagemedia. By way of example only, storage system 34 can be provided forreading from and writing to a non-removable, non-volatile magnetic media(not shown and typically called a “hard drive”). Although not shown, amagnetic disk drive for reading from and writing to a removable,non-volatile magnetic disk (e.g., a “floppy disk”), and an optical diskdrive for reading from or writing to a removable, non-volatile opticaldisk such as a CD-ROM, DVD-ROM, or other optical media can be provided.In such instances, each can be connected to bus 18 by one or more datamedia interfaces. As will be further depicted and described below,memory 28 may include at least one program product having a set (e.g.,at least one) of program modules that are configured to carry out thefunctions of embodiments of the invention.

The embodiments of the invention may be implemented as a computerreadable signal medium, which may include a propagated data signal withcomputer readable program code embodied therein (e.g., in baseband or aspart of a carrier wave). Such a propagated signal may take any of avariety of forms including, but not limited to, electro-magnetic,optical, or any suitable combination thereof. A computer readable signalmedium may be any computer readable medium that is not a computerreadable storage medium and that can communicate, propagate, ortransport a program for use by or in connection with an instructionexecution system, apparatus, or device.

Program code embodied on a computer readable medium may be transmittedusing any appropriate medium including, but not limited to, wireless,wireline, optical fiber cable, radio-frequency (RF), etc., or anysuitable combination of the foregoing.

Program/utility 40, having a set (at least one) of program modules 42,may be stored in memory 28 by way of example, and not limitation, aswell as an operating system, one or more application programs, otherprogram modules, and program data. Each of the operating system, one ormore application programs, other program modules, and program data orsome combination thereof, may include an implementation of a networkingenvironment. Program modules 42 generally carry out the functions and/ormethodologies of embodiments of the invention as described herein.

Computer system/server 12 may also communicate with one or more externaldevices 14 such as a keyboard, a pointing device, a display 24, etc.;one or more devices that enable a user to interact with computersystem/server 12; and/or any devices (e.g., network card, modem, etc.)that enable computer system/server 12 to communicate with one or moreother computing devices. Such communication can occur via Input/Output(I/O) interfaces 22. Still yet, computer system/server 12 cancommunicate with one or more networks such as a local area network(LAN), a general wide area network (WAN), and/or a public network (e.g.,the Internet) via network adapter 20. As depicted, network adapter 20communicates with the other components of computer system/server 12 viabus 18. It should be understood that although not shown, other hardwareand/or software components could be used in conjunction with computersystem/server 12. Examples include, but are not limited to: microcode,device drivers, redundant processing units, external disk drive arrays,RAID systems, tape drives, and data archival storage systems, etc.

Referring now to FIG. 2, illustrative cloud computing environment 50 isdepicted. As shown, cloud computing environment 50 comprises one or morecloud computing nodes 10 with which local computing devices used bycloud consumers, such as, for example, personal digital assistant (PDA)or cellular telephone 54A, desktop computer 54B, laptop computer 54C,and/or automobile computer system 54N may communicate. Nodes 10 maycommunicate with one another. They may be grouped (not shown) physicallyor virtually, in one or more networks, such as private, community,public, or hybrid clouds as described hereinabove, or a combinationthereof. This allows cloud computing environment 50 to offerinfrastructure, platforms, and/or software as services for which a cloudconsumer does not need to maintain resources on a local computingdevice. It is understood that the types of computing devices 54A-N shownin FIG. 2 are intended to be illustrative only and that computing nodes10 and cloud computing environment 50 can communicate with any type ofcomputerized device over any type of network and/or network addressableconnection (e.g., using a web browser).

Referring now to FIG. 3, a set of functional abstraction layers providedby cloud computing environment 50 (FIG. 2) is shown. It should beunderstood in advance that the components, layers, and functions shownin FIG. 3 are intended to be illustrative only and embodiments of theinvention are not limited thereto. As depicted, the following layers andcorresponding functions are provided:

Hardware and software layer 60 includes hardware and softwarecomponents. Examples of hardware components include mainframes. In oneexample, IBM® zSeries® systems and RISC (Reduced Instruction SetComputer) architecture based servers. In one example, IBM pSeries®systems, IBM xSeries® systems, IBM BladeCenter® systems, storagedevices, networks, and networking components. Examples of softwarecomponents include network application server software. In one example,IBM WebSphere® application server software and database software. In oneexample, IBM DB2® database software. (IBM, zSeries, pSeries, xSeries,BladeCenter, WebSphere, and DB2 are trademarks of International BusinessMachines Corporation registered in many jurisdictions worldwide.)

Virtualization layer 62 provides an abstraction layer from which thefollowing examples of virtual entities may be provided: virtual servers;virtual storage; virtual networks, including virtual private networks;virtual applications and operating systems; and virtual clients.

In one example, management layer 64 may provide the functions describedbelow. Resource provisioning provides dynamic procurement of computingresources and other resources that are utilized to perform tasks withinthe cloud computing environment. Metering and pricing provide costtracking as resources are utilized within the cloud computingenvironment, and billing or invoicing for consumption of theseresources. In one example, these resources may comprise applicationsoftware licenses. Security provides identity verification for cloudconsumers and tasks, as well as protection for data and other resources.User portal provides access to the cloud computing environment forconsumers and system administrators. Service level management providescloud computing resource allocation and management such that requiredservice levels are met. Service Level Agreement (SLA) planning andfulfillment provides pre-arrangement for, and procurement of, cloudcomputing resources for which a future requirement is anticipated inaccordance with an SLA.

Workloads layer 66 provides examples of functionality for which thecloud computing environment may be utilized. Examples of workloads andfunctions which may be provided from this layer include: mapping andnavigation; software development and lifecycle management; virtualclassroom education delivery; data analytics processing; transactionprocessing; and end-to end provisioning. As mentioned above, all of theforegoing examples described with respect to FIG. 3 are illustrativeonly, and the invention is not limited to these examples.

It is understood all functions of the present invention as describedherein are typically performed by the end-to-end provisioning function,which can be tangibly embodied as modules of program code 42 ofprogram/utility 40 (FIG. 1). However, this need not be the case. Rather,the functionality recited herein could be carried out/implemented and/orenabled by any of the layers 60-66 shown in FIG. 3.

It is reiterated that although this disclosure includes a detaileddescription on cloud computing, implementation of the teachings recitedherein are not limited to a cloud computing environment. Rather, theembodiments of the present invention are intended to be implemented withany type of clustered computing environment now known or laterdeveloped. Moreover, although the illustrative embodiment of FIGS. 4-6discusses a GPFS-based cloud storage configuration, this need not be thecase. Rather, the teachings recited herein could be applied to any typeof storage configuration.

Referring now to FIG. 4, an illustrative architecture according to anembodiment of the present invention is shown. As shown, a set (at leastone) of clients 100 can communicate with a set of interface nodes 104(e.g., GPFS nodes) over a network connection 102 (e.g., LAN, WAN, etc.).Set of interface nodes 104 then communicate via interconnects 106 (e.g.,high sped interconnects) with a set of storage nodes 108. As furthershown, set of storage nodes 108 then interface with a set of storagesubsystems 112 (e.g., Redundant Array of Independent Disks (RAID)) viafiber channel network 110. As discussed above, the embodiments of thepresent invention provide end-to-end provisioning for storagearchitectures such as that shown in FIG. 4. Among other things, suchembodiments will discover resources present in a given architecture,take into account workload requirements and configurations, develop aset of plans for provisioning the architecture based on the workloadrequirements and configurations, and develop scripts for executing theset of plans.

Referring now to FIG. 5, a process flow diagram according to anembodiment of the present invention is shown. Specifically, FIG. 5depicts various components and/or elements that perform the functions ofthe embodiments of the present invention. Among other things, one taskperformed by provisioning engine P7 is to determine/provide storageconfiguration(s) (e.g., a GPFS configuration) that can accommodate: (1)the space, performance and other requirements of the specified workloads(e.g., workload requirements P6); (2) different resource configurationssuch as storage subsystem configuration P1, fabric configuration P2, andhost/HBA configuration P3; and models such as subsystem models P5.

The first step in the automated planning comprises discovery of allavailable resources (like storage subsystems, interconnection fabric,servers, etc.) and their configurations P1-P3. The performance andresiliency of the storage cloud may be dependent on the composition andconfiguration of different logical and physical entities like storagearrays, Logical Unit Numbers (LUNs), zoning, I/O servers, etc. Asfurther shown, configurations P1-P3 and models P5 can be received byend-to-end modeling system P4, which will generate a set of models thatis utilized by provisioning planning engine P7 along with workloadrequirements P6 to generate a set of plans such as (GPFS) cluster planP8, network fabric plan P9, storage subsystem plan P10. In a typicalembodiment, workload requirements P6 can be specified as follows:

Capacity Requirements: Space, quota.

Performance Requirements: Input/Output per Second (IOPS), read/writeratio, random/sequential ratio, cache hit ratio, etc.

Workload types: Online Transaction Processing (OLTP), Scientific,Warehouse, backup, etc.

In one embodiment, the plan(s) P8-10 can call for either extending anexisting GPFS cluster (by adding new storage nodes and/or LUNs, or bycreating a completely new GPFS cluster. As indicated above, automatedplanning hereunder includes discovery of all available resources (e.g.,storage subsystems, interconnection fabric, servers, etc.) and theirconfigurations. The provisioning planning engine P7 determines thenumber and configuration of these entities based on their availabilitiesand capabilities, the workload requirements and industry best practices.

It is understood that the indentations and subsection indicators shownbelow are for clarity and ease of reading only, and are not intended tolimit any of the teachings recited herein. At the end of the planningprocess, the provisioning planning engine P7 produces a list ofconfiguration plans that comprises:

-   -   i) The number, size and type of LUNs shown in the formula below.        The LUNs are placed such that their loads are spread across        multiple storage arrays, pools, device adapters, etc. The type        of the arrays and the RAID levels are selected such that the set        of LUNs can cumulatively handle the workload performance        requirements. Since GPFS places data across all available disks,        the provisioning planning engine P7 tries to maintain uniformity        in the size and type of LUNs within a GPFS cluster. This ensures        uniform distribution of load.

${\sum\limits_{i}^{{Set}\mspace{14mu} {of}\mspace{14mu} {workloads}}C_{i}} \leq {\sum\limits_{j}^{{Set}\mspace{14mu} {of}\mspace{14mu} {LUNs}}L_{j}}$

-   -   ii) The provisioning planning engine P7 determines the number        and types of GPFS nodes as shown in the formulation below.        Depending on the workload requirements, the provisioning        planning engine P7 configures these nodes as interface nodes,        network shared disk (NSD) servers, quorum node, or manager node.        Clients connect to interface nodes and these types of nodes        access the shared disk via NSD servers. There are various types        of manager nodes: cluster, file system and token.        -   Let N=Number of NSD servers        -   Let S_(i)=I/O capacity of each NSD server        -   Let M=Number of Workloads        -   Let W_(i)=Average I/O requirement of workload ‘i’

${\sum\limits_{i}^{N}S_{i}} \geq {\sum\limits_{i}^{M}W_{i}}$

-   -   The above formulation calculates the minimum number of NSD        servers required for a given set of workloads. In order to        introduce certain levels of fault tolerance, system        administrators may want to introduce some redundancy at the NSD        server level. Let the redundancy factor be ‘r’. The final number        of NSD server deployed is [r.M]    -   The number/configuration of interface nodes can also be        calculated in a similar fashion. In this case, the I/O capacity        of an interface node is the maximum I/O traffic that can be        supported between the clients and the interface nodes.    -   iii) Thereafter, LUNs are masked/mapped to the NSD servers.        Depending on the fabric connectivity and resiliency        requirements, LUNs can be mapped to all or a subset of NSD        servers. The provisioning planning engine P7 determines complete        a end-to-end data path from HBA (Host Bus Adapter) ports in the        NSD servers to storage subsystem FC (fiber channel) ports.    -   GPFS permits a maximum of 8 NSD servers per LUN. In most cases,        it is not necessary to have that many mappings. But for load        balancing and fault tolerance reasons, the provisioning planning        engine P7 configures two or more paths between the LUNs and the        NSD servers. The exact fiber channel ports involved in the        mapping are determined based on existing load on the ports and        corresponding fabric and fiber channel switches. To provide        redundancy (e.g., in the event NSD server failure), the        provisioning planning engine P7 maps each LUN to at least 2 NSD        servers.

In addition to plans P8-P10, output provided by provisioning planningengine P7 could comprise: (1) a proposed storage architectureconfiguration: storage volumes, LUN mapping/masking, multipathconfiguration, zoning configuration, etc; (2) a proposed GPFS clusterconfiguration: network shared disk (NSD), NSD servers, Interface node,GPFS manager nodes, etc.; and/or (3) a proposed GPFS configuration: filesystems, GPFS storage pools, etc.

Based on user or system selection, the provisioning planning engine P7generates a set of deployment scripts to automate the installation ofdrivers and tools, creation of new entities and configuration ofexisting ones (collectively shown as coordinated and automateddeployment P11. This simplifies the cloud provisioning process, reducescost and the possibility of making errors. In a typical embodiment, thescripts are generated by provisioning planning engine while the plansare being generated or shortly thereafter. Specifically, as courses ofactions (e.g., configuration changes) for the plans are determined,correlating commands will be generated for carrying out the changes.Along these lines, commands/scripts can be generated for any elementdenoted in a plan. In providing this functionality, appropriate commandsfor carrying out plan elements can be determined based upon a lookuptable (e.g., that associates actions/changes with commands and or APIcalls), a rules engine, etc.

The process of generating and executing scripts can also be referred toas deployment management that generally comprises: invoking appropriateApplication Programming Interfaces (APIs); and utilizing command linetools to deploy the plans. For the teachings herein, this would meaninvoking web service APIs in Storage Resource Management (SRM) toolssuch as Tivoli® Storage Productivity Center (TPC), which providesdifferent APIs. Among other things, Tivoli can be used to create newLUNs, configure LUN mapping/masking, fiber channel zoning, etc. Tivoliand related terms are trademarks of IBM Corp. in the United Statesand/or other countries. For cluster creation and other GPFSconfiguration management tasks, GPFS command line tools can be utilized.Shown below are some examples:

% mmcrcluster—N node1,node2%

% mmcrnsd—F diskDesriptorFile; where diskDesriptorFile containsinformation about the two LUNS created by TPC

% mmcrfs fs1 nsd1,nsd2

Referring now to FIG. 6, a method flow diagram according to anembodiment of the present invention is shown. As depicted, in step S1, aset of workload requirements and a set of system resource configurationsfor a storage cloud are accessed. This typically involves discoveringavailable resources associated with the storage cloud. Specifically, theresource discovery can include determining a number and a configurationof each of the available resources. In step S2, a set of plans forprovisioning the storage cloud is generated. In general, each of the setof plans provide an adjustment of the set of system resourceconfigurations so that the set of workload requirements are met. Forexample, the set of plans can: describe a configuration of a GeneralParallel File System (GPFS) cluster associated with the storage cloud;provide a mapping of LUNs to network shared disk (NSD) nodes; identify anumber and a type of GPFS nodes associated with the storage cloud;and/or identify a number, a size, and a type of logical unit numbers(LUNs) associated with the storage cloud. Output provided based ongeneration of the plans can comprise, for example, a storage areanetwork (SAN) configuration, a GPFS cluster configuration, and/or a GPFSconfiguration. Regardless, in step S3, a set of scripts is generated tocarry out the set of plans. Along these lines, the set of scripts isconfigured to orchestrate a deployment and a configuration of a set ofhardware and software components associated with the storage cloud. Instep S4, the plans are executed using the scripts.

While shown and described herein as a storage cloud provisioningsolution, it is understood that the invention further provides variousalternative embodiments. For example, in one embodiment, the inventionprovides a computer-readable/useable medium that includes computerprogram code to enable a computer infrastructure to provide storagecloud provisioning functionality as discussed herein. To this extent,the computer-readable/useable medium includes program code thatimplements each of the various processes of the invention. It isunderstood that the terms computer-readable medium or computer-useablemedium comprise one or more of any type of physical embodiment of theprogram code. In particular, the computer-readable/useable medium cancomprise program code embodied on one or more portable storage articlesof manufacture (e.g., a compact disc, a magnetic disk, a tape, etc.), onone or more data storage portions of a computing device, such as memory28 (FIG. 1) and/or storage system 34 (FIG. 1) (e.g., a fixed disk, aread-only memory, a random access memory, a cache memory, etc.).

In another embodiment, the invention provides a method that performs theprocess of the invention on a subscription, advertising, and/or feebasis. That is, a service provider, such as a Solution Integrator, couldoffer to provide storage cloud provisioning functionality. In this case,the service provider can create, maintain, support, etc., a computerinfrastructure, such as computer system 12 (FIG. 1) that performs theprocesses of the invention for one or more consumers. In return, theservice provider can receive payment from the consumer(s) under asubscription and/or fee agreement and/or the service provider canreceive payment from the sale of advertising content to one or morethird parties.

In still another embodiment, the invention provides acomputer-implemented method for storage cloud provisioning. In thiscase, a computer infrastructure, such as computer system 12 (FIG. 1),can be provided and one or more systems for performing the processes ofthe invention can be obtained (e.g., created, purchased, used, modified,etc.) and deployed to the computer infrastructure. To this extent, thedeployment of a system can comprise one or more of: (1) installingprogram code on a computing device, such as computer system 12 (FIG. 1),from a computer-readable medium; (2) adding one or more computingdevices to the computer infrastructure; and (3) incorporating and/ormodifying one or more existing systems of the computer infrastructure toenable the computer infrastructure to perform the processes of theinvention.

As used herein, it is understood that the terms “program code” and“computer program code” are synonymous and mean any expression, in anylanguage, code, or notation, of a set of instructions intended to causea computing device having an information processing capability toperform a particular function either directly or after either or both ofthe following: (a) conversion to another language, code, or notation;and/or (b) reproduction in a different material form. To this extent,program code can be embodied as one or more of: an application/softwareprogram, component software/a library of functions, an operating system,a basic device system/driver for a particular computing device, and thelike.

A data processing system suitable for storing and/or executing programcode can be provided hereunder and can include at least one processorcommunicatively coupled, directly or indirectly, to memory elementsthrough a system bus. The memory elements can include, but are notlimited to, local memory employed during actual execution of the programcode, bulk storage, and cache memories that provide temporary storage ofat least some program code in order to reduce the number of times codemust be retrieved from bulk storage during execution. Input/outputand/or other external devices (including, but not limited to, keyboards,displays, pointing devices, etc.) can be coupled to the system eitherdirectly or through intervening device controllers.

Network adapters also may be coupled to the system to enable the dataprocessing system to become coupled to other data processing systems,remote printers, storage devices, and/or the like, through anycombination of intervening private or public networks. Illustrativenetwork adapters include, but are not limited to, modems, cable modems,and Ethernet cards.

The foregoing description of various aspects of the invention has beenpresented for purposes of illustration and description. It is notintended to be exhaustive or to limit the invention to the precise formdisclosed and, obviously, many modifications and variations arepossible. Such modifications and variations that may be apparent to aperson skilled in the art are intended to be included within the scopeof the invention as defined by the accompanying claims.

What is claimed is:
 1. A computer-implemented method for end-to-endprovisioning of storage clouds, comprising: accessing a set of workloadrequirements and a set of system resource configurations for a set ofhardware and software components associated with a storage cloud;generating a set of plans for provisioning the storage cloud to meet theset of workload requirements, the set of plans proposing an adjustmentbased on at least one formulaic calculation, the formulaic calculationcomprising:${\sum\limits_{i}^{N}S_{i}} \geq {\sum\limits_{i}^{M}W_{i}}$generating a set of scripts to carry out the set of plans, the set ofscripts being configured to orchestrate a deployment and a configurationof the set of hardware and software components; deploying a set ofnetwork shared disk (NSD) servers, wherein the number of NSD servers inthe set of NSD servers equals a product of r and M; wherein “N” is anumber of NSD servers, “S_(i)” is an input/output (I/O) capacity of eachNSD server, “M” is a number of workloads, “W_(i)” is an average I/Orequirement of a workload “i”, and “r” is a redundancy factor.
 2. Themethod of claim 1, the set of plans describing a configuration of aGeneral Parallel File System (GPFS) cluster associated with the storagecloud.
 3. The method of claim 1, further comprising discoveringavailable resources associated with the storage cloud.
 4. The method ofclaim 3, the discovering comprising determining a number and aconfiguration of each of the available resources.
 5. The method of claim1, the set of configuration plans identifying a number, a size, and atype of logical unit numbers (LUNs) associated with the storage cloud.6. The method of claim 1, the set of configuration plans identifying anumber and a type of GPFS nodes associated with the storage cloud. 7.The method of claim 1, the set of configuration plans providing amapping of LUNs to network shared disk (NSD) nodes.
 8. The method ofclaim 1, further comprising generating output based on the set of plans,the output comprising a storage area network (SAN) configuration, a GPFScluster configuration, and a GPFS configuration.
 9. A system forend-to-end provisioning of storage clouds, comprising: a bus; aprocessor coupled to the bus; and a memory medium coupled to the bus,the memory medium comprising instructions to: access a set of workloadrequirements and a set of system resource configurations for a set ofhardware and software components associated with a storage cloud;generate a set of plans for provisioning the storage cloud to meet theset of workload requirements, the set of plans proposing an adjustmentbased on at least one formulaic calculation, the formulaic calculationcomprising:${\sum\limits_{i}^{N}S_{i}} \geq {\sum\limits_{i}^{M}W_{i}}$ generatea set of scripts to carry out the set of plans, the set of scripts beingconfigured to orchestrate a deployment and a configuration of the set ofhardware and software components; deploy a set of network shared disk(NSD) servers, wherein the number of NSD servers in the set of NSDservers equals a product of r and M; wherein “N” is a number of NSDservers, “S_(i)” is an input/output (I/O) capacity of each NSD server,“M” is a number of workloads, “W_(i)” is an average I/O requirement of aworkload “i”, and “r” is a redundancy factor.
 10. The system of claim 9,the set of plans describing a configuration of a General Parallel FileSystem (GPFS) cluster associated with the storage cloud.
 11. The systemof claim 9, the memory medium further comprising instructions todiscover available resources associated with the storage cloud.
 12. Thesystem of claim 11, the memory medium further comprising instructions todetermine a number and a configuration of each of the availableresources.
 13. The system of claim 9, the set of configuration plansidentifying: a number, a size, and a type of logical unit numbers (LUNs)associated with the storage cloud; and a number and a type of GPFS nodesassociated with the storage cloud.
 14. The system of claim 13, the setof configuration plans further providing a mapping of LUNs to networkshared disk (NSD) nodes.
 15. The system of claim 9, the memory mediumfurther comprising instructions to generate output based on the set ofplans, the output comprising a storage area network (SAN) configuration,a GPFS cluster configuration, and a GPFS configuration.
 16. A computerprogram product for end-to-end provisioning of storage clouds, thecomputer program product comprising a computer readable storage media,and program instructions stored on the computer readable storage media,to: access a set of workload requirements and a set of system resourceconfigurations for a set of hardware and software components associatedwith a storage cloud; generate a set of plans for provisioning thestorage cloud to meet the set of workload requirements, the set of plansproposing an adjustment based on at least one formulaic calculation, theformulaic calculation comprising:${\sum\limits_{i}^{N}S_{i}} \geq {\sum\limits_{i}^{M}W_{i}}$ generatea set of scripts to carry out the set of plans, the set of scripts beingconfigured to orchestrate a deployment and a configuration of the set ofhardware and software components; deploy a set of network shared disk(NSD) servers, wherein the number of NSD servers in the set of NSDservers equals a product of r and M; wherein “N” is a number of NSDservers, “S_(i)” is an input/output (I/O) capacity of each NSD server,“M” is a number of workloads, “W_(i)” is an average I/O requirement of aworkload “i”, and “r” is a redundancy factor.
 17. The computer programproduct of claim 16, the set of plans describing a configuration of aGeneral Parallel File System (GPFS) cluster associated with the storagecloud.
 18. The computer program product of claim 16, further comprisingprogram instructions stored on the computer readable storage media todiscover available resources associated with the storage cloud.
 19. Thecomputer program product of claim 18, further comprising programinstructions stored on the computer readable storage media to determinea number and a configuration of each of the available resources.
 20. Thecomputer program product of claim 16, the set of configuration plansidentifying: a number, a size, and a type of logical unit numbers (LUNs)associated with the storage cloud; and a number and a type of GPFS nodesassociated with the storage cloud.
 21. The computer program product ofclaim 20, the set of configuration plans further providing a mapping ofLUNs to network shared disk (NSD) nodes.
 22. The computer programproduct of claim 16, further comprising program instructions stored onthe computer readable storage media to generate output based on the setof plans, the output comprising a storage area network (SAN)configuration, a GPFS cluster configuration, and a GPFS configuration.23. A method for deploying a system for end-to-end provisioning ofstorage clouds, comprising: providing a computer infrastructure beingoperable to: access a set of workload requirements and a set of systemresource configurations for a set of hardware and software componentsassociated with a storage cloud; generating a set of plans forprovisioning the storage cloud to meet the set of workload requirements,the set of plans proposing an adjustment based on at least one formulaiccalculation, the formulaic calculation comprising:${\sum\limits_{i}^{N}S_{i}} \geq {\sum\limits_{i}^{M}W_{i}}$ generatea set of scripts to carry out the set of plans, the set of scripts beingconfigured to orchestrate a deployment and a configuration of the set ofhardware and software components; deploy a set of network shared disk(NSD) servers, wherein the number of NSD servers in the set of NSDservers equals a product of r and M; wherein “N” is a number of NSDservers, “S_(i)” is an input/output (I/O) capacity of each NSD server,“M” is a number of workloads, “W_(i)” is an average I/O requirement of aworkload “i”, and “r” is a redundancy factor.